use of org.apache.kafka.common.metrics.stats.Percentiles in project kafka by apache.
the class MetricsBench method main.
public static void main(String[] args) {
long iters = Long.parseLong(args[0]);
Metrics metrics = new Metrics();
try {
Sensor parent = metrics.sensor("parent");
Sensor child = metrics.sensor("child", parent);
for (Sensor sensor : Arrays.asList(parent, child)) {
sensor.add(metrics.metricName(sensor.name() + ".avg", "grp1"), new Avg());
sensor.add(metrics.metricName(sensor.name() + ".count", "grp1"), new WindowedCount());
sensor.add(metrics.metricName(sensor.name() + ".max", "grp1"), new Max());
sensor.add(new Percentiles(1024, 0.0, iters, BucketSizing.CONSTANT, new Percentile(metrics.metricName(sensor.name() + ".median", "grp1"), 50.0), new Percentile(metrics.metricName(sensor.name() + ".p_99", "grp1"), 99.0)));
}
long start = System.nanoTime();
for (int i = 0; i < iters; i++) parent.record(i);
double ellapsed = (System.nanoTime() - start) / (double) iters;
System.out.println(String.format("%.2f ns per metric recording.", ellapsed));
} finally {
metrics.close();
}
}
use of org.apache.kafka.common.metrics.stats.Percentiles in project apache-kafka-on-k8s by banzaicloud.
the class MetricsTest method testSimpleStats.
@Test
public void testSimpleStats() throws Exception {
ConstantMeasurable measurable = new ConstantMeasurable();
metrics.addMetric(metrics.metricName("direct.measurable", "grp1", "The fraction of time an appender waits for space allocation."), measurable);
Sensor s = metrics.sensor("test.sensor");
s.add(metrics.metricName("test.avg", "grp1"), new Avg());
s.add(metrics.metricName("test.max", "grp1"), new Max());
s.add(metrics.metricName("test.min", "grp1"), new Min());
s.add(new Meter(TimeUnit.SECONDS, metrics.metricName("test.rate", "grp1"), metrics.metricName("test.total", "grp1")));
s.add(new Meter(TimeUnit.SECONDS, new Count(), metrics.metricName("test.occurences", "grp1"), metrics.metricName("test.occurences.total", "grp1")));
s.add(metrics.metricName("test.count", "grp1"), new Count());
s.add(new Percentiles(100, -100, 100, BucketSizing.CONSTANT, new Percentile(metrics.metricName("test.median", "grp1"), 50.0), new Percentile(metrics.metricName("test.perc99_9", "grp1"), 99.9)));
Sensor s2 = metrics.sensor("test.sensor2");
s2.add(metrics.metricName("s2.total", "grp1"), new Total());
s2.record(5.0);
int sum = 0;
int count = 10;
for (int i = 0; i < count; i++) {
s.record(i);
sum += i;
}
// prior to any time passing
double elapsedSecs = (config.timeWindowMs() * (config.samples() - 1)) / 1000.0;
assertEquals(String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs), count / elapsedSecs, metrics.metrics().get(metrics.metricName("test.occurences", "grp1")).value(), EPS);
// pretend 2 seconds passed...
long sleepTimeMs = 2;
time.sleep(sleepTimeMs * 1000);
elapsedSecs += sleepTimeMs;
assertEquals("s2 reflects the constant value", 5.0, metrics.metrics().get(metrics.metricName("s2.total", "grp1")).value(), EPS);
assertEquals("Avg(0...9) = 4.5", 4.5, metrics.metrics().get(metrics.metricName("test.avg", "grp1")).value(), EPS);
assertEquals("Max(0...9) = 9", count - 1, metrics.metrics().get(metrics.metricName("test.max", "grp1")).value(), EPS);
assertEquals("Min(0...9) = 0", 0.0, metrics.metrics().get(metrics.metricName("test.min", "grp1")).value(), EPS);
assertEquals("Rate(0...9) = 1.40625", sum / elapsedSecs, metrics.metrics().get(metrics.metricName("test.rate", "grp1")).value(), EPS);
assertEquals(String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs), count / elapsedSecs, metrics.metrics().get(metrics.metricName("test.occurences", "grp1")).value(), EPS);
assertEquals("Count(0...9) = 10", (double) count, metrics.metrics().get(metrics.metricName("test.count", "grp1")).value(), EPS);
}
use of org.apache.kafka.common.metrics.stats.Percentiles in project apache-kafka-on-k8s by banzaicloud.
the class MetricsTest method testPercentiles.
@Test
public void testPercentiles() {
int buckets = 100;
Percentiles percs = new Percentiles(4 * buckets, 0.0, 100.0, BucketSizing.CONSTANT, new Percentile(metrics.metricName("test.p25", "grp1"), 25), new Percentile(metrics.metricName("test.p50", "grp1"), 50), new Percentile(metrics.metricName("test.p75", "grp1"), 75));
MetricConfig config = new MetricConfig().eventWindow(50).samples(2);
Sensor sensor = metrics.sensor("test", config);
sensor.add(percs);
Metric p25 = this.metrics.metrics().get(metrics.metricName("test.p25", "grp1"));
Metric p50 = this.metrics.metrics().get(metrics.metricName("test.p50", "grp1"));
Metric p75 = this.metrics.metrics().get(metrics.metricName("test.p75", "grp1"));
// record two windows worth of sequential values
for (int i = 0; i < buckets; i++) sensor.record(i);
assertEquals(25, p25.value(), 1.0);
assertEquals(50, p50.value(), 1.0);
assertEquals(75, p75.value(), 1.0);
for (int i = 0; i < buckets; i++) sensor.record(0.0);
assertEquals(0.0, p25.value(), 1.0);
assertEquals(0.0, p50.value(), 1.0);
assertEquals(0.0, p75.value(), 1.0);
// record two more windows worth of sequential values
for (int i = 0; i < buckets; i++) sensor.record(i);
assertEquals(25, p25.value(), 1.0);
assertEquals(50, p50.value(), 1.0);
assertEquals(75, p75.value(), 1.0);
}
use of org.apache.kafka.common.metrics.stats.Percentiles in project kafka by apache.
the class MetricsTest method testPercentiles.
@Test
public void testPercentiles() {
int buckets = 100;
Percentiles percs = new Percentiles(4 * buckets, 0.0, 100.0, BucketSizing.CONSTANT, new Percentile(metrics.metricName("test.p25", "grp1"), 25), new Percentile(metrics.metricName("test.p50", "grp1"), 50), new Percentile(metrics.metricName("test.p75", "grp1"), 75));
MetricConfig config = new MetricConfig().eventWindow(50).samples(2);
Sensor sensor = metrics.sensor("test", config);
sensor.add(percs);
Metric p25 = this.metrics.metrics().get(metrics.metricName("test.p25", "grp1"));
Metric p50 = this.metrics.metrics().get(metrics.metricName("test.p50", "grp1"));
Metric p75 = this.metrics.metrics().get(metrics.metricName("test.p75", "grp1"));
// record two windows worth of sequential values
for (int i = 0; i < buckets; i++) sensor.record(i);
assertEquals(25, (Double) p25.metricValue(), 1.0);
assertEquals(50, (Double) p50.metricValue(), 1.0);
assertEquals(75, (Double) p75.metricValue(), 1.0);
for (int i = 0; i < buckets; i++) sensor.record(0.0);
assertEquals(0.0, (Double) p25.metricValue(), 1.0);
assertEquals(0.0, (Double) p50.metricValue(), 1.0);
assertEquals(0.0, (Double) p75.metricValue(), 1.0);
// record two more windows worth of sequential values
for (int i = 0; i < buckets; i++) sensor.record(i);
assertEquals(25, (Double) p25.metricValue(), 1.0);
assertEquals(50, (Double) p50.metricValue(), 1.0);
assertEquals(75, (Double) p75.metricValue(), 1.0);
}
use of org.apache.kafka.common.metrics.stats.Percentiles in project kafka by apache.
the class MetricsTest method shouldPinLargerValuesToMax.
@Test
public void shouldPinLargerValuesToMax() {
final double min = 0.0d;
final double max = 100d;
Percentiles percs = new Percentiles(1000, min, max, BucketSizing.LINEAR, new Percentile(metrics.metricName("test.p50", "grp1"), 50));
MetricConfig config = new MetricConfig().eventWindow(50).samples(2);
Sensor sensor = metrics.sensor("test", config);
sensor.add(percs);
Metric p50 = this.metrics.metrics().get(metrics.metricName("test.p50", "grp1"));
sensor.record(max + 100);
sensor.record(max + 100);
assertEquals(max, (double) p50.metricValue(), 0d);
}
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